A knowledge discovery approach to supporting crime prevention

Sheng Tun Li, Fu Ching Tsai, Shu Ching Kuo, Yi Chung Cheng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Recently, the increasing volume crimes have been one of the most serious issues in Taiwan. The Ministry of Internal Affairs has been working out a project to examine the public security index with red, yellow, purple, green, blue five lights in order to strengthen the public security. For analyzing and predicting huge linguistic data which evolve with time, we propose a novel fuzzy self-organization map network to uncover crime trend and use association rule to discover the hidden causal effects between two different criminal time series data. The fuzzy self-organization model integrates the features of dealing with clustering and linguistic data of SOM and fuzzy logic, respectively. We analyze the clustering results on distinguishing different trends of each criminal category and find rules relating patterns in a time series to other patterns, for the purpose of specifying the instructions of police human resources planning. The resulting findings can facilitate the development of a useful decision-support tool for helping decision makers determine appropriate law enforcement strategies.

Original languageEnglish
Title of host publicationProceedings of the 9th Joint Conference on Information Sciences, JCIS 2006
DOIs
Publication statusPublished - 2006
Event9th Joint Conference on Information Sciences, JCIS 2006 - Taiwan, ROC, Taiwan
Duration: 2006 Oct 82006 Oct 11

Publication series

NameProceedings of the 9th Joint Conference on Information Sciences, JCIS 2006
Volume2006

Other

Other9th Joint Conference on Information Sciences, JCIS 2006
Country/TerritoryTaiwan
CityTaiwan, ROC
Period06-10-0806-10-11

All Science Journal Classification (ASJC) codes

  • General Engineering

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